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A Longitudinal Investigation of Posttraumatic Growth in AdultPatients Undergoing Treatment for Acute Leukemia
Suzanne C. Danhauer • Gregory B. Russell • Richard G. Tedeschi •
Michelle T. Jesse • Tanya Vishnevsky • Kristin Daley • Suzanne Carroll •
Kelli N. Triplett • Lawrence G. Calhoun • Arnie Cann • Bayard L. Powell
Published online: 28 June 2012
� Springer Science+Business Media, LLC 2012
Abstract An acute leukemia diagnosis can be an extre-
mely stressful experience for most patients. Posttraumatic
growth (PTG) is positive psychological change experi-
enced following a struggle with highly challenging life
circumstances. The current study is the first longitudinal
investigation of predictors of PTG and distress in adult
acute leukemia patients undergoing induction chemother-
apy. Findings suggest that these patients report PTG, and
levels of PTG appear to increase over the weeks following
leukemia diagnosis and induction chemotherapy. Variables
associated with higher total PTG scores over time included
greater number of days from baseline, younger age, and
greater challenge to core beliefs. Variables associated with
higher distress included greater number of days from
baseline, greater perceived cancer threat, higher symptom
severity, and lower spiritual well-being. Results underscore
the critical role that examination of one’s core beliefs may
play in the development of PTG over time.
Keywords Leukemia � Posttraumatic growth �Adjustment � Quality of life � Hematologic malignancies
Introduction
Diagnosis and treatment of acute leukemia is an extremely
stressful experience for most patients (Greenberg et al.,
1997; Hjermstad et al., 1999; Molassiotis, van den Akker,
Milligan, Goldman, & Boughton, 1996; Montgomery,
Pocock, Titley, & Lloyd, 2003; Persson, Hallberg, &
Ohlsson, 1997; Sasaki et al., 2000; Zittoun, Achard,
&Ruszniewski, 1999). Patients with both acute lympho-
cytic leukemia (ALL) and acute myelogenous leukemia
(AML) usually present with signs and/or symptoms of
failure to produce normal blood and bone marrow cells.
These symptoms include fever from inability to fight
infections, bleeding and bruising from very low platelet
counts, weakness/fatigue, and other symptoms of anemia.
AML is the most common type of acute leukemia in adults
(80%), and ALL accounts for about 20% of acute leukemia
cases. The sudden manifestation of leukemia symptoms
requiring immediate, intensive treatments, and prolonged
hospital stays contribute to the highly stressful nature of
this disease (Caudell, 1996; Xuereb & Dunlop, 2003).
Following diagnosis, patients are immediately hospital-
ized for induction chemotherapy, for a period of 4–6 weeks
(and sometimes longer for complications). Induction ther-
apy is the initial phase of treatment with the goal of
decreasing the number of leukemia cells to undetectable
levels and restoring normal blood cells. Treatment for
acute leukemia includes significant risk for neutropenia (a
severely low number of white blood cells associated with
high risk of infection) and sepsis (the presence of patho-
genic infectious organisms or their toxins in the blood and
tissues) within the first few months of treatment (Lesko,
1998). Other common side effects of chemotherapy
include, but are not limited to, anemia, mucositis (sores in
the mouth and gastrointestinal tract), alopecia (hair loss),
S. C. Danhauer � G. B. Russell � M. T. Jesse � T. Vishnevsky �K. Daley � S. Carroll � K. N. Triplett � B. L. Powell
Comprehensive Cancer Center of Wake Forest University,
Winston-Salem, NC, USA
S. C. Danhauer (&)
Department of Social Sciences & Health Policy, Wake Forest
School of Medicine, Winston-Salem, NC 27157, USA
e-mail: [email protected]
R. G. Tedeschi � M. T. Jesse � T. Vishnevsky � K. Daley �K. N. Triplett � L. G. Calhoun � A. Cann
UNC Charlotte, Charlotte, NC, USA
123
J Clin Psychol Med Settings (2013) 20:13–24
DOI 10.1007/s10880-012-9304-5
headaches, nausea, anorexia, fatigue, and increased vul-
nerability to illness/infection (Caudell, 1996; Persson et al.,
2001; Valley & Balmer, 2000; Zittoun et al., 1999).
Symptoms and treatment-related side effects are strongly
linked to quality of life in acute leukemia patients (Persson
et al., 2001).
Patients with acute leukemia also experience psycho-
logical difficulties including depressive symptoms (Mo-
lassiotis et al., 1996; Montgomery et al., 2003; Sasaki et al.,
2000; Zittoun et al., 1999), reduced quality of life (Persson
et al., 2001), mood disturbances (Molassiotis et al., 1996),
sleep difficulties (Edman, Larsen, Hagglund, & Gardulf,
2001; Sasaki et al., 2000; Zittoun et al., 1999), and fear of
recurrence following treatment (Greenberg et al., 1997;
Black & White, 2005). Although this diagnosis contributes
to a highly stressful experience for most patients with acute
leukemia, relatively little research has been conducted
during treatment for this patient group.
An increasing amount of research has demonstrated that
despite substantial distress associated with the diagnosis of
a life-threatening illness, patients commonly report psy-
chological growth and enhanced well-being following
cancer diagnosis and treatment (Andrykowski et al., 2005;
Bellizzi, 2004; Bellizzi & Blank, 2006; Cordova et al.,
2007; Lelorain, Bonnaud-Antignac, & Florin, 2010).
Posttraumatic growth (PTG) is defined as ‘‘positive psy-
chological change experienced as a result of a struggle with
highly challenging life circumstances’’ (Tedeschi & Cal-
houn, 2004). These changes have qualities such as
improved interpersonal relating, a greater appreciation for
life, a sense of personal strength, new life possibilities, and
spiritual change (Tedeschi & Calhoun, 1996). In a recent
description of the process by which PTG emerges in the
aftermath of trauma, Calhoun, Cann, and Tedeschi (2010)
emphasize the action of several variables: the extent to
which core beliefs or the ‘‘assumptive world’’ (Janoff-
Bulman, 1992) is challenged; intrusive/brooding and
deliberate/reflective rumination; the ability to manage
emotional distress; self-disclosure and social reactions to
disclosure; and cultural influences on belief systems. In this
model, an event such as a cancer diagnosis can set in
motion a questioning of core beliefs that becomes rumi-
native, with self-disclosure to supportive others making
possible more deliberate or reflective rumination, which in
turn can allow for changes in core beliefs that yield PTG. A
recent study showed core beliefs to be related to both
intrusive and deliberate rumination which were, in turn,
differentially related to PTG and distress (Triplett, Tede-
schi, Calhoun, Cann, & Reeve, 2011). Core belief chal-
lenge appears to be more strongly implicated in the process
of PTG than other variables are (Lindstrom, Cann, Cal-
houn, & Tedeschi, 2011).
In the cancer literature, PTG has been more strongly
related to psychosocial variables than to demographic or
medical variables (Lelorain et al., 2010; Stanton, Bower, &
Low, 2006), with two notable exceptions being longer time
since diagnosis and younger age (Cordova, Cunningham,
Carlson, & Andrykowski, 2001; Manne et al., 2004; Ran-
sonm, Sheldon, & Jacobsen, 2008; Sears, Stanton, &
Danoff-Burg, 2003; Smith, Dalen, Bernard, & Baumgart-
ner, 2008). Findings from one qualitative study showed
personal growth in leukemia patients (Daiter, Larson,
Weddington, & Ultmann, 1988), and another study that
assessed PTG in patients with hematologic malignancies
(including acute leukemia) found similar levels of PTG as
in other cancer populations (Carboon, Anderson, Pollard,
Szer, & Seymour, 2005). No study to date, however, has
examined PTG longitudinally in a sample comprised solely
of acute leukemia patients.
The purpose of this study was to document emotional
functioning of patients undergoing induction chemotherapy
for acute leukemia. Specific goals were to investigate
predictors of PTG and distress in adult acute leukemia
patients. Clear and present threats to mortality might also
lead to attempts to use spiritual coping mechanisms when
other ways of coping with such a threat fail. People higher
in spirituality may be better able to comfort themselves and
therefore engage in the constructive and deliberate cogni-
tive processing that can support PTG. We hypothesized
that higher levels of PTG would be associated with greater
self-reported levels of spiritual well-being, greater cancer-
related rumination, greater perceived threat from cancer,
and greater challenge to core belief systems. Following the
process described in the model of PTG, scores on the
Posttraumatic Growth Inventory were expected to increase
with a greater challenge to core beliefs produced by sig-
nificant levels of threat, and that necessitated a reconsid-
eration through rumination that was initially intrusive and
later more deliberate and reflective. Given that PTG has
been shown to be relatively orthogonal to measures of
distress, it is important to measure distress separately. We
also examined the relationship of the same variables in a
model using distress as the outcome to examine whether
variables associated with distress are similar to those
associated with PTG. No directional hypotheses for distress
were made.
Method
Design
To address these questions, we conducted a longitudinal
study of adult acute leukemia patients (n = 66)
14 J Clin Psychol Med Settings (2013) 20:13–24
123
hospitalized for induction chemotherapy at Wake Forest
Baptist Medical Center (WFBMC). Patients completed up
to three packets of questionnaires: Time 1 (T1; week 0 or
within 7 days of diagnosis and/or admission), Time 2 (T2;
weeks 5–6 or prior to discharge from the hospital if patient
was discharged prior to week 5), and Time 3 (T3;
approximately weeks 9–13 upon readmission for consoli-
dation chemotherapy (additional treatment to eliminate
leukemia cells that cannot be detected and to prevent
relapse).
Sample (Eligibility Criteria)
Participants were eligible if they: (1) were adults C18 years
of age; (2) had a new diagnosis of ALL or AML; (3) were
hospitalized for induction chemotherapy; and (4) spoke
adequate English to understand informed consent form,
complete questionnaires and converse with study staff.
Recruitment
Study participants were approached to participate in the
study within 7 days of their admission to the hospital or
within 7 days of their diagnosis of acute leukemia,
whichever occurred later. (Some patients were admitted
following diagnosis at outside hospitals while others were
admitted to our medical center and then received an acute
leukemia diagnosis.) They were identified by the Clinical
Nurse Specialist on the Leukemia Service and then
recruited by a member of the research team.
Measures
The following instruments were used to measure basic
demographic, clinical, and psychosocial variables at T1, T2,
and T3 with the exception of demographic information
(collected at T1 only) and chart information (collected at T3
Table 1 Description of study measures and timing of administration
Timing of
administration
Response scale Range of
possible
scores
Meaning of scores Cronbach’s
a for
current
studyT1 T2 T3
Outcome measures
PTGI X X X 0 (I did not experience this change) to
5 (I experienced this change to a
great deal)
0–105 Higher levels of perceived
growth
0.95
POMS–TMD X X X 1 (not at all) to 5 (extremely) 0–148 Higher levels of mood
disturbance
0.96
Predictor variables
MDASI X X X 0 (Not present) to 10 (As bad as you
can imagine)
0–190 More severe symptoms; Greater
interference in life
0.91
WHIIRS X X X 0 (No, not in the past 4 weeks) 4 (Yes,
5 or more times a week)
0–20 Greater difficulties to sleeping 0.89
FACIT-Sp X X X 0 (Not at all) to 4 (very much) 0–48 Higher levels of spiritual well-
being
0.86
Social constraint
scale
X X X 1 (Almost never) to 5 (Almost always) 10–50 Greater experience of social
constraints
0.81
Cancer-related
rumination
X X X 1 (Not at all) to 4 (A great deal) 6–24a; 5–20b Higher levels of rumination 0.88a; 0.80b
Perceived threat
from cancer
X X X 0 (Not stressful at all) to 4 (Extremely
stressful)
0–16 Greater perceived
cancer threat
0.84
Core beliefs
inventory
X X X 0 (Not at all) to 5 (To a very great
degree)
0–45 Greater disruption to
core beliefs
0.89
Additional variables
Sociodemographic X
Chart review X
a Reflects intrusive ruminationb Reflects deliberate rumination
PTGI = Posttraumatic Growth Inventory, POMS-TD = Profile of Mood States-Short Form Total Mood Disturbance subscale
MDASI = M.D. Anderson Symptom Inventory, WHIRS = Women’s Health Initiative Insomnia Rating Scale, FACIT-Sp = Functional
Assessment of Chronic Illness Therapy-Spirituality
J Clin Psychol Med Settings (2013) 20:13–24 15
123
only). Detailed information for each of the study measures is
summarized in Table 1. Study measures included:
Outcome Measures
Posttraumatic Growth Inventory (PTGI)
(Tedeschi & Calhoun, 1996)
The PTGI is a 21-item scale that measures the degree of
reported positive changes experienced in the struggle with
major life crises. The scale includes items that assess the
degree to which the individual reports specific positive
changes attributed to the struggle with trauma. It includes 5
empirically-derived factors of PTG: Relating to Others,
New Possibilities, Appreciation of Life, Personal Strength,
and Spiritual Change. Cronbach’s alpha for the total score
has consistently reported in the high range from a = .91 to
0.93 (Anderson & Lopez-Baez, 2008; Bates, Trajstman, &
Jackson, 2004; Brunet, McDonough, Hadd, Crocker, &
Sabiston, 2009; Linley, Andrews, & Joseph, 2007; Michael
& Snyder, 2005; Morris, Shakespeare-Finch, Rieck, &
Newberry, 2005; Taku, Cann, Calhoun, & Tedeschi, 2008)
and self-reports of growth tend to be corroborated by others
(Moore et al., 2011; Weiss, 2002). Sample items include:
‘‘I changed my priorities about what is important in life,’’
and ‘‘I can better appreciate each day.’’ The total score was
used in the current study for all analyses. Analyses were
not conducted for individual PTGI factors due to the small
sample size.
The Profile of Mood States-Short Form (POMS-SF)
(Shacham, 1983)
The POMS-SF is a 37-item adjective checklist to assess for
current mood. Participants respond whether they have
experienced moods (e.g., unhappy, confused, tense) over
the past week. A total mood disturbance (TMD) score was
used to measure overall psychological distress. The POMS-
SF has sound psychometric qualities (Baker, Denniston,
Zabora, Polland, & Dudley, 2002; Curran, Andrykowski, &
Studts, 1995).
Predictor Variables
Sociodemographic and Medical Information
The following information was collected at baseline: age,
race/ethnicity, marital/partner status, educational history,
income, religious affiliation/involvement, and employment
status. The patient’s medical record was the source of data
for cancer diagnosis.
M.D. Anderson Symptom Inventory (MDASI)
(Cleeland et al., 2000)
The MDASI is a 13-item self-report measure of the
severity and impact of cancer-related symptoms such as
‘‘Your pain at its worst’’ and ‘‘Your nausea at its worst.’’ Its
core items contain symptoms that account for the majority
of symptom distress reported by cancer patients in active
treatment; fatigue, pain, nausea, disturbed sleep, distress,
shortness of breath, lack of appetite, drowsiness, dry
mouth, sadness, emesis, feeling bloated, and numbness/
tingling. The MDASI is designed for simplicity, brevity,
and acceptability to very ill patients.
Women’s Health Initiative Insomnia Rating Scale
(WHIIRS) (Levine et al., 2005)
The WHIIRS was used to measure sleep quality. This 5-
item scale is designed to measure sleep initiation and
maintenance in the past 4 weeks. The scale assesses sleep
problems including, but not limited to the ability to fall
asleep, sleep quality, and fatigue and includes items such as
‘‘Did you have trouble falling asleep,’’ and ‘‘Did you wake
up several times a night?’’ This scale has acceptable levels
of reliability and validity.
Functional Assessment of Chronic Illness
Therapy—Spirituality (FACIT-Sp) (Peterman,
Fitchett, Brady, Cella, & Hernandez, 2002)
The FACIT-Sp assesses spiritual well-being. It was
developed with an ethnically diverse cancer population,
contains 12 items and 2 subscales (the role of faith in ill-
ness and a sense of meaning/peace), and has good to
excellent psychometric properties. One characteristic of
this scale is that the wording of items does not assume a
belief in God. Therefore, it can be comfortably completed
by atheist or agnostic respondents, yet it taps into both
traditional religiousness dimensions (faith factor) and
spiritual dimensions (meaning and peace factor). Sample
items include: ‘‘I feel peaceful’’ and ‘‘I have a reason for
living.’’
Social Constraint Scale (Lepore, Silver,
Wortman, & Wayment, 1996)
This 10-item social constraint measure assesses the degree
to which cancer patients perceive that others are unwilling
or unable to provide support to them in the form of concern
and listening (Lepore et al., 1996). A set of five questions is
asked twice, once with regard to the ‘‘most important
person’’ in the respondent’s life and once with regard to
‘‘other people’’ and includes items such as ‘‘How often did
16 J Clin Psychol Med Settings (2013) 20:13–24
123
you feel as though you had to keep your feelings about
your experience with leukemia to yourself because they
made (important person/other people) uncomfortable,’’ and
‘‘When you talked about your experience with leukemia,
how often did (important person/other people) give you the
idea (s)he didn’t want to talk about it?’’ Higher scores
denote greater experience of social constraints. Factor
analysis supports a unitary factor for the ten items (Lepore
et al., 1996).
Cancer-Related Rumination (Calhoun, Cann,
Tedeschi, & McMillan, 2000)
The Cancer-Related Rumination Scale is a 12-item modi-
fied version of the Rumination Inventory developed by
Calhoun et al. (2000). The items focus on the degree to
which the individual reports intrusive thoughts about can-
cer such as ‘‘I have thoughts about cancer and I could not
get rid of them.’’ The scale also measures deliberate
thinking about the diagnosis such as, ‘‘I have thought about
how to best manage the challenges associated with can-
cer.’’ A factor analysis of the baseline data identified 2
separate factors: intrusive rumination (6 variables) and
deliberate rumination (5 variables), with 1 variable asso-
ciated with neither. The mean scores of the intrusive
rumination and deliberate rumination subscales were used
in study analyses.
Perceived Threat from Cancer
The perceived threat measure was developed for this study
and includes the following 4 items that assess the degree to
which patients perceive that their lives and personal
integrity are threatened by their cancer: ‘‘How stressful has
having cancer been for you?’’; ‘‘To what extent has cancer
been a threat to your life or physical health?’’; ‘‘To what
extent has cancer disrupted your plans for the future?’’; and
‘‘To what extent has cancer been a threat to your under-
standing of who you are as an individual?’’ The four items
for this measure are consistent with the focus of previous
studies on these aspects of the cancer experience (Horlick-
Jones, 2011; Leung & Esplen, 2010; Montgomery &
McCrone, 2010; Thombre & Sherman, 2010).
Core Beliefs Inventory (CBI) (Cann et al., 2010)
The CBI includes 9 items originally developed for this
study in order to measure the degree of disruption to var-
ious aspects of the assumptive world (Janoff-Bulman,
1992). It quantifies the amount an individual examines core
beliefs and assumptions about the world when undergoing
a significant life experience. Specifically, the amount a
person examines his/her beliefs about whether there is
order to the world, his/her importance in that world, and
that people and the world are generally ‘good’ or ‘fair.’
Participants rate the extent to which the experience with
leukemia led them to seriously examine things such as
‘‘The degree to which things that happen to people are
fair,’’ and ‘‘Your expectations for your future.’’ Items are
summed for a total disruption score where higher indicates
greater perceived disruption due to the event.
Clinical Chart Review
Clinical information was obtained from the patient’s
medical record. Specifically, this information included
Table 2 Demographic and clinical characteristics of the sample at
baseline (N = 66)
Demographic/clinical characteristics n (%)
Age [mean (SD)] 48.3 (15.2)
Range 19–81
Diagnosis
ALL 14 (21.2)
AML 52 (78.8)
Education
High school diploma or less 28 (42.4)
Some college/vocational training 21 (31.8)
College graduate 17 (25.8)
Income (total annual)1
\$35,000 23 (39.7)
$35,000–$49,999 10 (17.2)
$50,000–$99,999 18 (31.0)
$100,000? 7 (12.1)
Relationship Status
Not married/partnered 18 (27.3)
Married/partnered 48 (72.7)
Importance of religion in your life
Not at all important 2 (3.0)
Not very important 1 (1.5)
Somewhat important 5 (7.6)
Very important 58 (87.9)
Religious attendance
Frequent (1 or more times per week) 31 (47.0)
Moderate/occasionally (several times per year) 21 (31.8)
Rare/never (once a year or never) 14 (21.2)
Chemotherapy regimen
Cytarabine plus daunorubicin (with or without
etoposide)
41 (62.1)
Cytarabine, daunorubicin plus ATRA 8 (12.1)
Daunorubicin, Vicristine, Prednisone, Asparaginase 14 (21.2)
±Cyclophosphamide
Other 3 (4.5)
1 Reported family income had 8 missing values
J Clin Psychol Med Settings (2013) 20:13–24 17
123
leukemia diagnosis, date of diagnosis, date of admission,
date of discharge from hospital for induction chemother-
apy, previous cancer history, prescribed treatment regimen,
performance status, and complications experienced during
the hospital stay. Table 2 shows the treatment regimens for
study participants. The most common regimen used for
AML induction was a standard combination of cytarabine
as a continuous infusion for 7 days in conjunction with
daunorubicin on days 1–3, with or without etoposide, also
on days 1–3; eight patients with acute promyelocytic leu-
kemia, a subset of AML, received cytarabine as a 7-day
continuous infusion beginning on day 3, daunorubicin for
4 days beginning on day 3 and all-trans retinoic acid
(ATRA) given orally from day 1 until patient achieved
remission. The primary regimen for ALL included dau-
norubicin for 3 days, vincristine weekly for 4 weeks,
prednisone for 1 week or longer depending on age, and
asparaginase given twice weekly for 6 doses beginning on
day 5, with or without cyclophosphamide on day one, again
depending on age.
Data Analysis
Repeated measures mixed effects models were used to
assess the effects of demographic, medical, and psycho-
social variables on PTGI and POMS–TMD scores over
the course of the study period. Since the study measures
were not completed on a pre-determined fixed schedule, a
random intercept model was used. The random intercept
model fits a separate intercept and regression line for each
participant. The repeated measures approach allows the
ability to evaluate the effect of each independent measure
over the period of observation and estimate its average
effect on a participant. Using this approach, a partici-
pant’s score at any point during the study interval can be
estimated. A complete model was fit, with the indepen-
dent variables selected through an initial analysis of the
Pearson’s correlation coefficient between PTGI and
POMS–TMD scores and the broader list of psychosocial
measures. The remaining psychosocial variables were
most strongly correlated (p \ .05) to the PTGI and/or
POMS–TMD scores. For consistency and comparability
between measures, the same independent measures were
used for both the PTGI and POMS–TMD outcomes.
Predictor variables included in the full model included
demographics (age, education, race, marital status, reli-
gious attendance), medical (diagnosis, symptom severity),
time (days from completion of baseline measures), and
psychosocial (MDASI severity score, FACIT-Sp, social
constraints, cancer-related rumination as deliberate and
intrusive rumination, perceived threat, WHIIRS, and CBI)
variables.
Results
Over the course of three years, 134 potentially eligible
patients were approached for study participation. Of these,
78 (58.2% of those approached) provided informed con-
sent, and 66 newly diagnosed acute leukemia patients
completed the baseline questionnaire. (See study flow of
participants in Fig. 1.) The median age of the sample
(N = 66) was 50 years old (range 19–81). Additional
descriptive information is available in Table 2.
Of these 66, 40 (60.6%) completed the questionnaire at
T2 (mean number of days from baseline = 31.2,
SD = 11.0, range 13–63, median 28), and 37 (56.1%)
completed the questionnaire at T3 (mean number of days
from baseline = 75.1, SD = 32.2; range 40–166; median
69). Of those who refused or could not continue, the main
reasons for non-participation were lack of interest (61%),
medical issues/feeling too sick (21%), or altered mental
status (10%). Participants who completed all study mea-
sures were similar to dropouts in terms of age (p = .20),
religious attendance (p = .07), education (p = .95), and
relationship status (p = .99).
Of the 66 participants, 63 completed the PTGI at base-
line (mean score = 58.2; SD = 26.8). The remaining three
reported they were either too fatigued to complete the
measure or did not find the items applicable so soon after
diagnosis. At T2, 40 completed the PTGI (mean
score = 66.3; SD = 22.5), and at T3, 37 completed the
PTGI (mean score = 73.1; SD = 20.4). The 37 partici-
pants who completed the study had mean PTGI scores of
63.4 (SD = 26.1) and 65.3 (SD = 22.5) for T1 and T2,
respectively. For distress, 66 completed the POMS–TMD
at baseline (mean score = 54.0; SD = 31.2). At T2, 40
completed the POMS–TMD (mean score = 48.7;
SD = 32.0), and at T3, 36 completed the POMS–TMD
(mean score = 43.0; SD = 28.0). The 36 participants who
completed the study had mean POMS–TMD scores of 57.8
(SD = 28.4) and 49.5 (SD = 33.9) for T1 and T2,
respectively.
Analysis of covariance models were derived through a
process of correlating individual subscales of other psy-
chosocial measures with the total PTGI and POMS–TMD
scores, assessing the baseline correlations. (See Table 3 for
intercorrelations for all study variables.) Variables that
were significant (p \ .05) with either outcome were
included in the full models. MDASI severity, intrusive
rumination, perceived threat, and core beliefs were corre-
lated with both total PTGI and POMS–TMD scores.
Deliberate rumination was associated only with PTGI.
FACIT-Sp, social constraints, and WHIIRS were correlated
only with POMS–TMD. Control measures, such as age and
other demographics as noted previously, were added to the
models as adjustment factors.
18 J Clin Psychol Med Settings (2013) 20:13–24
123
Description of Regression Results
Variables in the full models for total PTGI and POMS–
TMD scores were the same for comparability between
measures. (See Table 4 for final models.) For total PTGI
scores, the significantly associated measures were days
from baseline (p = .03), age (p = .03), deliberate rumi-
nation (p \ .001), and core beliefs (p \ .01). These find-
ings indicate greater number of days from baseline,
younger age, increased deliberate rumination, and greater
challenge to one’s core beliefs were associated with higher
PTGI scores over time. For POMS–TMD, days since
baseline (p = \.01), perceived threat (p = \.001), delib-
erate rumination (p \ .01), intrusive rumination (p \ .01)
and FACIT-Sp (p \ .0001) were significantly associated
with the outcome measure. These findings indicate that
fewer days from baseline, greater perceived threat, lower
deliberate rumination, higher intrusive rumination, and
lower spiritual well-being scores were all associated with
increased distress scores. Further, results in Table 4
Fig. 1 Flow of participants through the study
J Clin Psychol Med Settings (2013) 20:13–24 19
123
demonstrate the significant changes in both PTGI and
POMS–TMD scores over time. By examining the results
for days since baseline, one can see that each additional
day during the study period was associated with a 0.11 unit
increase (on average) in PTGI score and a 0.12 unit
decrease (on average) in POMS–TMD score.
Discussion
The findings of this study suggest that patients newly
diagnosed with acute leukemia develop PTG and that
levels of PTG appear to increase over the weeks following
diagnosis and induction chemotherapy, suggesting that
Table 3 Correlations between study variables at baseline
Variable 1 2 3 4 5 6 7 8 9
1. PTGI
2. POMS–TMD 0.08
3. MDASI-severity 0.21 0.73**
4. WHIIRS 0.15 0.42** 0.37**
5. FACIT-Sp -0.004 -0.70** -0.35** -0.37**
6. Social constraints 0.12 0.34** 0.15 0.03 -0.29*
7. Deliberate rumination 0.61** -0.08 0.06 0.06 0.25* -0.01
8. Intrusive rumination 0.29* 0.66** 0.51** 0.39** -0.45** 0.10 0.27*
9. Perceived threat 0.39** 0.74** 0.61** 0.33** -0.46** 0.15 0.28** 0.75**
10. Core beliefs 0.66** 0.39** 0.43** 0.24 -0.07 0.14 0.53** 0.55** 0.63**
N = 66 for POMS–TMD, MDASI-Severity, WHIIRS, FACIT-Sp; N = 65 for deliberate rumination and intrusive rumination; N = 64 for
perceived threat; N = 63 for PTGI and social constraints
* p B .05; ** p B .01
PTGI = Posttraumatic Growth Inventory, POMS-TD = Profile of Mood States-Short Form Total Mood Disturbance subscale, MDASI = M.D.
Anderson Symptom Inventory, WHIRS = Women’s Health Initiative Insomnia Rating Scale, FACIT-Sp = Functional Assessment of Chronic
Illness Therapy-Spirituality
Table 4 Analysis of total PTGI scores, POMS–TMD scores, and predictor variables
Covariate PTGI estimate (SE) PTGI p value POMS–TMD estimate (SE) POMS–TMD p value
Age -0.40 (0.16) .024 0.06 (0.11) .59
Education (compared to ‘some college’)
High school diploma or less 6.61 (5.19) .22 3.65 (3.51) .31
College graduate or higher -2.08 (5.98) .73 5.52 (4.05) .31
Marital status (non-partnered vs. partnered) -7.50 (5.49) .19 2.26 (3.81) .56
Race (White vs. Other) -0.60 (7.92) .94 -3.88 (5.41) .48
Religious attendance
Rare -4.73 (6.20) .46 4.08 (4.16) .34
Frequent 0.36 (5.15) .94 1.34 (3.45) .70
Medical
Days from baseline 0.11 (0.05) .021 -0.12 (0.04) .003
Diagnosis (ALL vs. AML) 1.53 (5.75) .79 -1.36 (3.87) .73
Psychosocial
Core beliefs 1.28 (0.32) .00008 0.14 (0.24) .56
Perceived threat -0.57 (2.56) .83 7.10 (1.95 .002
Social constraints 5.33 (3.30) .12 6.38 (2.38) .014
Spiritual well-being -0.008 (0.31) .98 -0.82 (0.22) .001
Symptom severity -0.03 (0.07) .68 0.43 (0.06) \.0001
WHIIRS sleep -0.34 (0.33) .32 0.32 (0.25) .22
Rumination-deliberate 9.71 (2.33) .0006 -5.67 (1.69) .003
Rumination-intrusive -2.93 (2.58) .27 6.81 (1.91) .002
20 J Clin Psychol Med Settings (2013) 20:13–24
123
some patients perceive improvements in various aspects of
their lives during intensive treatment for acute leukemia.
While PTGI scores were increasing, distress decreased
with greater number of days from baseline. The mean
scores on the total PTGI for the final assessment from this
study were noticeably higher than in other cancer patient
populations (Stanton et al., 2006). Specifically, our mean
PTGI total score for the final assessment was 72.8 while
other cancers have shown means scores ranging from the
low 40’s to the mid 60’s (Cordova et al., 2001; Oh et al.,
2004; Widows, Jacobsen, Booth-Jones, & Fields, 2005).
The results of this study indicated several factors that
were associated with higher PTG over time, including
greater number of days from baseline, younger age, greater
deliberate rumination and greater challenges to core
beliefs. These findings support prior cross-sectional
research suggesting that greater time since diagnosis (Sears
et al., 2003; Smith et al., 2008) is associated with higher
PTG. Several factors were also associated with higher
levels of distress, including fewer days from baseline,
greater perceived threat, lower deliberate rumination,
greater intrusive rumination, and lower spiritual well-
being. The finding that fewer days from baseline was
associated with higher levels of distress coincides with
previous research which suggests distress is greatest near
diagnosis (Barez, Blasco, Fernandez-Castro, & Viladrich,
2009; Henselmans, Sanderman, Baas, Smink, & Ranchor,
2009; Hoskins, Budin, & Maislin, 1996; Millar, Purusho-
tham, McLatchie, George, & Murray, 2005; Stanton et al.,
2002). In terms of perceived threat, it follows that partic-
ipants whose perceptions that their lives and personal
integrity are greatly threatened by cancer would be more
distressed than participants who perceive that cancer is less
of a threat to their lives. Finally, lower spiritual well-being
scores among those reporting the most distress in this study
may indicate that either the distress of diagnosis creates
some spiritual difficulty or that those with fewer spiritual
resources experience greater distress. This finding would
support previous research where spirituality has been found
to be a moderator of distress (Shapiro et al., 2001).
One of the most novel findings from these data is the
association of the degree of challenge to one’s core beliefs
with PTG. Tedeschi and Calhoun (2004) theorized that
disruptions to the assumptive world/core beliefs are what
set the stage for the potential growth that some individuals
report following a significant stressor. Specifically, they
hypothesized that growth does not occur due to the stressor
itself, but from the struggle and re-calibration of the indi-
vidual’s assumptive world following the stressor (Tedeschi
& Calhoun, 2004). Previous research that has attempted to
investigate this relationship has been predominantly cross-
sectional (Engelkemeyer & Marwit, 2008). The findings
of this study provide support for the critical role that
examination of one’s core beliefs may play in the devel-
opment of PTG over time. Specifically, the more an indi-
vidual reports examining and readjusting his/her core
beliefs about such things as his/her importance in the
world, whether the world is ‘good’ or ‘fair’ and whether
there is meaningfulness in the world over the course of
acute leukemia diagnosis and treatment, the more likely
(s)he is to report higher levels of PTG.
In accordance with this model of PTG, deliberate
rumination also plays a significant role in its development
in this sample. People experiencing high levels of PTG
report more deliberate rumination, while those who report
more distress simultaneously report lower levels of delib-
erate rumination and greater intrusive rumination. It
appears that a capability to reflect on ways to reconfigure
one’s core beliefs may be occurring among persons who
report more PTG.
This study had several limitations. First, the assessment
occurred over a relatively short period of time. Additional
follow-up assessments further out with regard to time
likely would provide more information regarding the
development of PTG. The issue of how long it may take for
threat to disrupt core beliefs and processing to produce
PTG is an empirical one. The sample here is quite different
from those in other studies that focus on retrospective
reports of growth. Here we are tracking it as it develops in
response to a clear and present threat to mortality. We
wished to see if a clear, serious and present threat of
mortality hastens this process. The fact that these patients
faced a severe threat is supported by the fact that many
patients in this sample died. Second, this study had a rel-
atively small sample size, and we lost a considerable
number of participants at follow-up. However, given the
study sample and the likely complications that these
patients experience during treatment for acute leukemia,
the number of participants lost was not unexpected for this
patient group. Third, the PTGI subscales were not exam-
ined separately which limits our understanding of the
process of PTG. Given our limited sample size, we were
concerned about the potential for Type 1 error and confined
our analysis to the PTGI total score. These limitations
notwithstanding, this study is the first of its kind to examine
PTG in a sample of adult patients with acute leukemia
longitudinally. Researchers in the PTG-cancer arena have
repeatedly emphasized the need for longitudinal studies of
PTG in patients with cancer (Aspinwall & MacNamara,
2005; Bower & Segerstrom, 2004; Stanton et al., 2006;
Tartaro et al., 2005).
These data demonstrate the development of PTG over
time in a sample of acute leukemia inpatients undergoing
highly intensive chemotherapy during a lengthy hospital
stay and suggest that, among other variables, challenge to
one’s core beliefs related to the cancer experience plays a
J Clin Psychol Med Settings (2013) 20:13–24 21
123
major role in the development of PTG. The study of PTG
points to possibilities for interventions and its potential
impact on long-term psychological and physical health.
However, as outlined in the debate on PTG (Aspinwall &
Tedeschi, 2010; Coyne, Tennen, & Ranchor, 2010; Coyne
& Tennen, 2010), we must proceed with caution with
designing interventions whose sole purpose is to develop
PTG. Instead, integrating an emphasis on discussion of
how the cancer experience challenges one’s core beliefs
(about oneself, relationships, the future, etc.) into psycho-
social interventions may facilitate the development of
PTG.
Acknowledgements The authors thank the physicians, physician
assistants, nurses, and most of all, the patients and their families, who
supported this work. Funding was provided by the Higginbotham
Memorial Cancer Patient Support Fund.
Conflict of Interest The authors declare no conflict of interest.
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